AI Chatbots Driving Fintech User Satisfaction via Trust and Service Quality

This study explores the impact of AI chatbots on user satisfaction in the fintech sector, emphasizing trust and service quality as primary drivers. The background underscores the increasing use of AI chatbots to enhance fintech user experiences. The objective is to investigate how Perceived Ease of Use (PEU), Perceived Usefulness (PU), Service Quality (SQ), and Trust (TR) shape user satisfaction. The research questions are: How do trust and service quality influence fintech user satisfaction, and what roles do PEU and PU play? Employing Structural Equation Modeling (SEM), the study analyzes data from 329 respondents. Findings indicate that trust is the strongest predictor of user satisfaction, followed by service quality, which significantly improves user experience. PEU exerts a moderate positive effect, while PU has a negligible or negative impact, suggesting trust and quality are more critical than perceived utility. These results highlight the pivotal role of trust in fintech platforms, with service quality as a key contributor. Limitations include the sample’s representativeness, which may limit generalizability. Future research should explore additional factors and longitudinal designs for deeper insights. The findings provide fintech companies with actionable strategies to optimize AI chatbot performance by prioritizing trust-building and high-quality service, contributing to enhanced user satisfaction in digital financial platforms.